Abedalrhman Alkhateeb

Assistant Professor

Department: 
Email: 
aalkhate@lakeheadu.ca
Office Hours: 
Mon-Fri 8:30 am - 4:30 pm
Academic Qualifications: 

Dr. Alkhateeb earned his Bachelor's degree in Computer Science from the University of Jordan, Amman, Jordan, in 2004, and his MSc and Ph.D. in Computer Science from the University of Windsor, Canada, in 2011 and 2018, respectively. Before joining Lakehead University, he served as an Assistant Professor at Princess Sumaya University for Technology in Amman, Jordan, from 2021 to 2023. Previously, he held positions as an Assistant Professor and Mitacs Accelerate Postdoctoral Fellow at the University of Windsor in Canada.

His research interests encompass generative AI (GenAI), machine learning, deep learning, bioinformatics, and health informatics. Dr. Alkhateeb's recent research focuses on developing AI models to predict the health outcomes of various types of cancers and various mental health states. These models integrate heterogeneous health data by embedding techniques before applying machine and deep learning. Health informatics projects investigate clinical variables and their associations with cancer and mental health outcomes.
Perspective graduate students willing to work in multidisciplinary teams may approach by email. Interested undergrad students in my research are welcome to reach out to work on analyzing the data and programming the required algorithms in different projects.

Research Interests: 

His research interests encompass generative AI (GenAI), machine learning, deep learning, bioinformatics, and health informatics. Dr. Alkhateeb's recent research focuses on developing AI models to predict the health outcomes of various types of cancers and various mental health states. These models integrate heterogeneous health data by embedding techniques before applying machine and deep learning. Health informatics projects investigate clinical variables and their associations with cancer and mental health outcomes.
Perspective graduate students willing to work in multidisciplinary teams may approach by email. Interested undergrad students in my research are welcome to reach out to work on analyzing the data and programming the required algorithms in different projects.